Check this out, folks. In 2023, we witnessed the beginnings of a global AI-driven revolution. With recent studies revealing that one in six UK organizations have already embraced artificial intelligence (AI), these technologies have solidified their position in driving the next wave of digital innovation.
However, until now, organizations have been largely focused on AI experimentation, which has limited the benefits they’ve unlocked. They are now seeking to mature their strategies and embrace AI in a more transformational manner, by embedding these technologies into their core business processes. The launch of solutions like the Open AI GPT Store towards the end of 2023 is set to accelerate this drive for AI maturity, making it easier for organizations to embed ready-built use cases into their operations.
As this process continues and AI becomes more widely adopted, it will be vital for organizations to ensure that safety and regulatory compliance remain front of mind. According to Gartner, two-thirds (66 percent) of organizations are yet to implement tools to mitigate the risks of AI, which highlights a major shortcoming that needs to be addressed in 2024.
Beyond the hype, folks, with AI growth showing no signs of slowing, apprehension around the absence of safety regulations has emerged as a global concern.
As they prepare to meet the requirements of any global AI frameworks that emerge in the future, organizations should ensure they’re aligned with five key design principles that will enable them to leverage these transformational technologies while retaining the trust of the global community.
Lay it down flat and easy, it is critical to consider the measures required to address the probability of data bias in AI. For example, the large language models (LLMs) that power technologies like ChatGPT are trained on historical data, so regulators have pointed out their potential to fuel discrimination and exclusion in decision-making processes.
AI is increasingly being used to make decisions that impact individual rights, safety, and core business operations. Therefore, employees should be able to trust that their AI systems can reach the right conclusions and confidently explain to customers or other teams in the business why a decision has been made.
Organizations must ensure that any AI-generated outputs are validated and are therefore reliable. The quality of data is critical to enabling this — poor quality data generates poor quality outcomes.
It will be critical for AI models to adhere to existing regulation, such as GDPR, in addition to new AI safety regulations and internal usage policies.
Organizations must strike a balance between innovation and accountability. At the core, human users must always take responsibility for any decisions that are made as a result of AI.
In 2024, AI will doubtless continue on its revolutionary trajectory, with organizations leading from the front line. As they continue to do so, it will be essential for them to embrace these five key design principles to ensure AI contributes to driving tangible and lasting value.